Abstract Convolutional Neural Networks (CNNs) are efficient tools for pattern recognition
applications. They have found applications in wireless communication systems such as …

This article focuses on automatic modulation classification (AMC) in wireless communication
systems. A convolutional neural network (CNN) with three layers is introduced for the AMC …

An efficient algorithm for earthmoving device recognition is essential for underground high
voltage cable protection in the mainland of China. Utilizing acoustic signals generated either …

This paper presents a novel hybrid extreme learning machine (ELM) with cuckoo search
algorithm (CSA) for the classification purposes of the digitally modulated signals, such as …

Automatic modulation recognition (AMR) is used in various domains—from general-purpose
communication to many military applications—thanks to the growing popularity of the …

Due to the stochastic nature of wireless channels, the received radio signal is noised during
transmission causing difficulty in classifying radio modulation categories. Deep learning …

Automatic modulation classification (AMC) is a process of automatic detection of modulation
format imposed on the received signal with no prior information (carrier, signal power, phase …

This paper investigates a vital issue in wireless communication systems, which is the
modulation classification. A proposed framework for modulation classification based on …

Multiple input multiple out (MIMO) cognitive radio offer the spatial degree of freedom that can
be used to share the spectrum with less interference via Precoding Technique. Many …

In this paper a low-complexity cyclostationary-based modulation classifier is presented,
which is capable of distinguishing between OFDM, GFSK and QPSK modulations. The …